This invention relates to the field of image scene analysis whereby wavelength data, emitted by numerous types of scenes and objects, are employed for obtaining information about the scene.
Fourier transform spectroscopy is one of the techniques that can be used in the area of medical tomography for tissue biopsy examination as an example, as well as in the identification and qualification of chemical compounds for environmental control. Detection and the precise location and nature of toxic waste and such conditions as diseased crops and forests have become very important. The detection and location of underground natural resources is another area of interest. In intelligence and battlefield applications, real time identification of the nature of various detected images, e.g. scenery, is of vital importance. Rapid real time image analysis can also be important for analyzing images of rapidly produced manufactured products during quality control. Thus, parallel optical digital processing would be highly desirable for many of these image analyzing applications.
Recently a special issue in Optical Engineering (Volume 37, 1998), has been published regarding area multi-spectra and hyper-spectra for remote scene and texture classification. The same techniques can also be applied for qualification of chemical compounds for environmental, intelligence, battlefield applications, and spectroscopic medical diagnosis. The general approach is to collect images in different wavelengths through the use the appropriate sensors, and then send these images to a data fusion center for detection and analysis. Various digital algorithmic approaches have been considered for analysis. Some of these approaches considered the use of bilinear logic and fuzzy logic; others considered the use of geometrical interpretation of a discrete wavelet transform. One of the most successful techniques used orthoganalization methods such as those of Gram-Schmidite (G-S) and the Karhunen-Loeve (K-L). While these techniques were impressive in performance, they required extensive time for calculation. Other approaches considered the Uses-Markov random field model, or neural network based on a pulse coupled neural network. The aforesaid referenced techniques employ digital algorithms and software designs which require extensive undesirable calculation time. In contrast, we employ holographic and non-holographic opto-electronic systems based on Fourier transform spectroscopy; see "Optics" Miles V. Klein, Edited by John Wiley (1969), Chapter 6 on interference spectroscopy p 219-237).